Youth & Adult Literacy Rates Datasets Link
Literacy rates refer to the percentage of individuals aged 15 and above who can read and write with understanding a short, simple statement on their everyday life. The dataset, available on Kaggle as two CSV files, delves into the literacy rates among youth and adults across diverse regions and countries. This extensive repository serves as a valuable resource for comprehending the literacy landscape, offering insights into various demographics such as age groups, genders, and geographical areas. Its multifaceted nature enables in-depth analyses, facilitating comparisons among regions, countries, and demographic segments. The dataset’s potential extends beyond raw figures; it stands as a crucial tool for policymakers, illustrating areas requiring targeted interventions to support literacy rates.
I chose this data because I’ve seen people around me who struggle with reading and writing. It made me curious about how things are now. I hope it can show where we need to do more to help people learn these important skills better.
library(dplyr): using for data manipulation
library(tidyverse): using to transform and better present data
library(ggplot2): using for data visualization and plotting charts
library(plotly): using for creating interactive web-based graphs
library(knitr): using for formatting tables
library(kableExtra): using for formatting tables and manipulate table styles
## Warning: package 'tidyverse' was built under R version 4.3.2
## Warning: package 'kableExtra' was built under R version 4.3.2
## Warning: package 'knitr' was built under R version 4.3.2
Reads csv files from a sub-folder to be examine & glimpse of data of 2 csv files
## Rows: 4,955
## Columns: 7
## $ index <dbl> 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, …
## $ Region <chr> "Central and Southern Asia", "Central and Southern Asi…
## $ Country <chr> "Afghanistan", "Afghanistan", "Afghanistan", "Afghanis…
## $ Year <dbl> 2011, 2011, 2011, 2011, 2011, 2011, 2011, 2011, 2011, …
## $ Age <chr> "15+", "15+", "15+", "15-24", "15-24", "15-24", "25-64…
## $ Gender <chr> "female", "male", "total", "female", "male", "total", …
## $ `Literacy rate` <dbl> 0.1761206, 0.4541710, 0.3174112, 0.3211322, 0.6187907,…
## Rows: 202
## Columns: 9
## $ Country <chr> "Afghanistan", "Albania", "Algeria",…
## $ Region <chr> "SA", "ECA", "MENA", "ECA", "SSA", "…
## $ `Sub-region` <chr> NA, "EECA", NA, "WE", "ESA", NA, NA,…
## $ `Least developed countries (LDC)` <chr> "LDC", NA, NA, NA, "LDC", NA, NA, NA…
## $ `Africa sub-regions` <chr> NA, NA, "Northern Africa", NA, "Sout…
## $ `Africa region` <chr> NA, NA, "All", NA, "All", NA, NA, NA…
## $ Total <dbl> 43, 98, 81, NA, NA, NA, NA, 99, NA, …
## $ Male <dbl> 55, 99, 87, NA, NA, NA, NA, 99, NA, …
## $ Female <dbl> 30, 98, 75, NA, NA, NA, NA, 99, NA, …
Following table provides the highest literacy rates of top 10 countries.
| Country Name | Mean Literacy Rate |
|---|---|
| Ukraine | 1.000 |
| Uzbekistan | 0.999 |
| San Marino | 0.999 |
| Latvia | 0.999 |
| Estonia | 0.999 |
| Lithuania | 0.998 |
| Kazakhstan | 0.997 |
| Belarus | 0.997 |
| Russian Federation | 0.997 |
| Cuba | 0.996 |
Following table provides the lowest literacy rates of 10 countries.
| Country Name | Mean Literacy Rate |
|---|---|
| Chad | 0.217 |
| Guinea | 0.259 |
| Niger | 0.278 |
| Mali | 0.308 |
| South Sudan | 0.308 |
| Sierra Leone | 0.333 |
| Burkina Faso | 0.334 |
| Benin | 0.335 |
| Afghanistan | 0.348 |
| Central African Republic | 0.371 |
The comparison of the highest literacy rates among the top 10 countries and the lowest literacy rates among another set of 10 countries highlights a stark contrast in educational achievements globally. The disparity between these two groups underscores the need for increased support and focused efforts to uplift literacy rates, particularly in regions or countries with lower rates. Examining the top 10 countries with the highest literacy rates offers valuable insight and can provide valuable benchmarks and best practices that could potentially be adopted or adapted by other countries improve their literacy rates. The identification of the bottom 10 countries in terms of literacy rates serves as a crucial reminder of the challenges faced by these regions. It emphasizes the urgency of implementing targeted interventions and comprehensive educational initiatives to uplift literacy levels.
The chart below shows that on average 64 and younger have higher literacy rate.
The analysis of the literacy rates based on age groups reveals a significant correlation between age and literacy across various regions and countries. The data illustrates that the age factor plays a crucial role in determining literacy levels, especially evident in the consistently lower literacy rates among individuals aged 65 and above compared to other age brackets. The dataset further highlights a categorization based on age groups, specifically focusing on the 15+ category, which encompasses individuals aged 15 and above. The variability in how countries collect and present their data regarding literacy rates is evident in the diverse age ranges used for data input. Some nations might report literacy rates under the broad category of 15+, while others might provide a breakdown into more specific age groups like 15-24 or 25-64.
Now, lets examine and break down by region. # Progress of a Region’s literacy rate over time
Analyzing literacy rates by region reveals intriguing trends, yet it also exposes inconsistencies in data reliability, particularly in certain regions where the data fluctuates significantly from year to year. This inconsistency poses a challenge when attempting to draw consistent conclusions or trends for these regions.
Breaking down the data into charts for each region allows for a more granular examination, highlighting distinct patterns and fluctuations. For instance, regions like Sub-Saharan Africa exhibit considerable variability in literacy rates from year to year.
while regional breakdowns offer valuable insights into literacy rate trends, the variability and inconsistency within certain regions underscore the need for more detailed analyses and a comprehensive understanding of the underlying factors contributing to these fluctuations.
| Country Name | Year | Mean Literacy Rate |
|---|---|---|
| Angola | 2014 | 0.589 |
| Benin | 2012 | 0.301 |
| Benin | 2018 | 0.368 |
| Botswana | 2013 | 0.775 |
| Botswana | 2014 | 0.784 |
| Burkina Faso | 2014 | 0.308 |
| Burkina Faso | 2018 | 0.360 |
| Burundi | 2014 | 0.556 |
| Burundi | 2017 | 0.624 |
| Cabo Verde | 2012 | 0.763 |
| Cabo Verde | 2015 | 0.781 |
| Cameroon | 2010 | 0.624 |
| Cameroon | 2018 | 0.699 |
| Central African Republic | 2010 | 0.370 |
| Central African Republic | 2018 | 0.371 |
| Chad | 2015 | 0.235 |
| Chad | 2016 | 0.199 |
| Comoros | 2012 | 0.441 |
| Comoros | 2018 | 0.514 |
| Congo | 2011 | 0.785 |
| Congo | 2018 | 0.794 |
| Côte d’Ivoire | 2012 | 0.383 |
| Côte d’Ivoire | 2014 | 0.389 |
| Côte d’Ivoire | 2018 | 0.425 |
| Democratic Republic of the Congo | 2012 | 0.700 |
| Democratic Republic of the Congo | 2016 | 0.717 |
| Equatorial Guinea | 2010 | 0.872 |
| Equatorial Guinea | 2014 | 0.888 |
| Eritrea | 2018 | 0.685 |
| Ethiopia | 2017 | 0.456 |
| Gabon | 2012 | 0.788 |
| Gabon | 2018 | 0.816 |
| Gambia | 2013 | 0.371 |
| Gambia | 2015 | 0.468 |
| Ghana | 2010 | 0.656 |
| Ghana | 2018 | 0.744 |
| Guinea | 2010 | 0.220 |
| Guinea | 2014 | 0.297 |
| Guinea-Bissau | 2014 | 0.418 |
| Kenya | 2014 | 0.745 |
| Kenya | 2018 | 0.770 |
| Lesotho | 2014 | 0.720 |
| Liberia | 2017 | 0.459 |
| Madagascar | 2012 | 0.672 |
| Madagascar | 2018 | 0.717 |
| Malawi | 2010 | 0.575 |
| Malawi | 2014 | 0.612 |
| Malawi | 2015 | 0.581 |
| Mali | 2010 | 0.284 |
| Mali | 2011 | 0.305 |
| Mali | 2015 | 0.308 |
| Mali | 2018 | 0.335 |
| Mauritania | 2017 | 0.493 |
| Mauritius | 2011 | 0.859 |
| Mauritius | 2012 | 0.918 |
| Mauritius | 2013 | 0.915 |
| Mauritius | 2014 | 0.925 |
| Mauritius | 2015 | 0.927 |
| Mauritius | 2016 | 0.932 |
| Mauritius | 2018 | 0.901 |
| Mozambique | 2015 | 0.515 |
| Mozambique | 2017 | 0.556 |
| Namibia | 2011 | 0.822 |
| Namibia | 2018 | 0.893 |
| Niger | 2012 | 0.278 |
| Nigeria | 2018 | 0.558 |
| Rwanda | 2010 | 0.604 |
| Rwanda | 2012 | 0.604 |
| Rwanda | 2014 | 0.626 |
| Rwanda | 2018 | 0.655 |
| Sao Tome and Principe | 2012 | 0.823 |
| Sao Tome and Principe | 2018 | 0.860 |
| Senegal | 2011 | 0.484 |
| Senegal | 2013 | 0.397 |
| Senegal | 2017 | 0.483 |
| Seychelles | 2010 | 0.899 |
| Seychelles | 2018 | 0.928 |
| Sierra Leone | 2013 | 0.296 |
| Sierra Leone | 2018 | 0.370 |
| South Africa | 2010 | 0.882 |
| South Africa | 2011 | 0.885 |
| South Africa | 2012 | 0.892 |
| South Africa | 2014 | 0.899 |
| South Africa | 2015 | 0.904 |
| South Africa | 2017 | 0.813 |
| South Sudan | 2018 | 0.308 |
| Swaziland | 2010 | 0.761 |
| Swaziland | 2018 | 0.822 |
| Togo | 2011 | 0.537 |
| Togo | 2015 | 0.575 |
| Uganda | 2010 | 0.660 |
| Uganda | 2012 | 0.640 |
| Uganda | 2018 | 0.703 |
| United Republic of Tanzania | 2010 | 0.654 |
| United Republic of Tanzania | 2012 | 0.716 |
| United Republic of Tanzania | 2015 | 0.714 |
| Zambia | 2010 | 0.768 |
| Zambia | 2018 | 0.817 |
| Zimbabwe | 2011 | 0.796 |
| Zimbabwe | 2014 | 0.876 |
| Country Name | Year | Mean Literacy Rate |
|---|---|---|
| Congo | 2011 | 0.785 |
| Mali | 2011 | 0.305 |
| Mauritius | 2011 | 0.859 |
| Namibia | 2011 | 0.822 |
| Senegal | 2011 | 0.484 |
| South Africa | 2011 | 0.885 |
| Togo | 2011 | 0.537 |
| Zimbabwe | 2011 | 0.796 |
| Country Name | Year | Mean Literacy Rate |
|---|---|---|
| Botswana | 2013 | 0.775 |
| Gambia | 2013 | 0.371 |
| Mauritius | 2013 | 0.915 |
| Senegal | 2013 | 0.397 |
| Sierra Leone | 2013 | 0.296 |
| Country Name | Year | Mean Literacy Rate |
|---|---|---|
| Brunei Darussalam | 2011 | 0.887 |
| Brunei Darussalam | 2018 | 0.934 |
| Cambodia | 2014 | 0.733 |
| Cambodia | 2015 | 0.767 |
| China | 2010 | 0.915 |
| China | 2018 | 0.951 |
| China, Macao Special Administrative Region | 2011 | 0.915 |
| China, Macao Special Administrative Region | 2016 | 0.940 |
| Indonesia | 2011 | 0.876 |
| Indonesia | 2014 | 0.907 |
| Indonesia | 2015 | 0.903 |
| Indonesia | 2016 | 0.906 |
| Indonesia | 2018 | 0.917 |
| Lao People’s Democratic Republic | 2011 | 0.544 |
| Lao People’s Democratic Republic | 2015 | 0.800 |
| Malaysia | 2010 | 0.863 |
| Malaysia | 2016 | 0.882 |
| Mongolia | 2010 | 0.975 |
| Mongolia | 2018 | 0.982 |
| Myanmar | 2016 | 0.739 |
| Philippines | 2013 | 0.952 |
| Philippines | 2015 | 0.975 |
| Singapore | 2010 | 0.926 |
| Singapore | 2011 | 0.981 |
| Singapore | 2012 | 0.979 |
| Singapore | 2013 | 0.980 |
| Singapore | 2014 | 0.981 |
| Singapore | 2015 | 0.950 |
| Singapore | 2016 | 0.983 |
| Singapore | 2017 | 0.980 |
| Singapore | 2018 | 0.981 |
| Thailand | 2010 | 0.958 |
| Thailand | 2013 | 0.913 |
| Thailand | 2015 | 0.913 |
| Timor-Leste | 2010 | 0.504 |
| Timor-Leste | 2018 | 0.580 |
| Viet Nam | 2018 | 0.939 |
| Region | Male | Female |
|---|---|---|
| Central and Southern Asia | 0.776 | 0.660 |
| Eastern and South-Eastern Asia | 0.915 | 0.851 |
| Europe and Northern America | 0.986 | 0.973 |
| Latin America and the Caribbean | 0.917 | 0.897 |
| Northern Africa and Western Asia | 0.895 | 0.807 |
| Oceania | 0.921 | 0.903 |
| Sub-Saharan Africa | 0.691 | 0.545 |
| Country | Male | Female | Difference |
|---|---|---|---|
| Malta | 93 | 96 | -3 |
| Mongolia | 98 | 99 | -1 |
| Seychelles | 95 | 96 | -1 |
| Eswatini | 88 | 89 | -1 |
| Uruguay | 98 | 99 | -1 |
| Argentina | 99 | 99 | 0 |
| Belarus | 100 | 100 | 0 |
| Brazil | 93 | 93 | 0 |
| Colombia | 95 | 95 | 0 |
| Costa Rica | 98 | 98 | 0 |
| Country | Male | Female | Difference |
|---|---|---|---|
| Afghanistan | 55 | 30 | 25 |
| Central African Republic | 50 | 26 | 24 |
| Benin | 54 | 31 | 23 |
| Mali | 46 | 26 | 20 |
| Nepal | 79 | 60 | 19 |
| Morocco | 83 | 65 | 18 |
| Nigeria | 71 | 53 | 18 |
| Burkina Faso | 50 | 33 | 17 |
| Sierra Leone | 52 | 35 | 17 |
| India | 82 | 66 | 16 |
The gender gap in literacy rates has been persistently evident over the years, showing a consistent gap between males and females. This longstanding trend underscores the necessity for targeted initiatives aimed at literacy among female. Additionally, there appears to be a crucial need for literacy programs specifically tailored for individuals aged 65 and above, acknowledging their unique learning needs and ensuring inclusivity across all age groups. One fundamental challenge highlighted in the dataset analysis is the inconsistency in data collection methods and accuracy across different years. This inconsistency poses a significant barrier in making accurate year-to-year comparisons and drawing conclusive insights. To facilitate more reliable and comprehensive analyses, there is a pressing need for standardized data collection protocols to be implemented consistently across regions and countries.